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                : Design, implementation and testing of new methods and algorithms so that SIESTA can harness the compute power of the latest generation of (pre-)exascale architectures and tackle novel scientific challenges 
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                machine translation relying on state-of-the-art deep neural models and architectures (LLMs). The work is to be carried out in the context of the Horizon Europe project IDEAL (Inclusive Democratic Engagement 
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                /Project: We are building an optimisation-driven framework that (i) makes AI agents reliably operate advanced scientific software (e.g., DFT, Wannierisation, and quantum-transport codes) and (ii) uses 
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